GIST: Greedy Independent Set Thresholding for Max-Min Diversification with Submodular Utility

This work studies a novel subset selection problem called *max-min diversification with monotone submodular utility* (MDMS), which has a wide range of applications in machine learning, e.g., data sampling and feature selection.